Operation model construction system, operation model construction method, and non-transitory computer readable storage medium

ABSTRACT

An operation model construction system includes a data acquisition unit that acquires operating data and external environment data of a moving object, an associated data accumulation unit that accumulates associated data obtained by classifying the external environment data into plural items and associating the operating data with the respective items, and an operation model construction unit that constructs plural operation models to operate the moving object, based on the associated data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2016-096674 filed May 13, 2016.

BACKGROUND Technical Field

The present invention relates to an operation model construction system,an operation model construction method, and a non-transitory computerreadable storage medium.

SUMMARY

According to an aspect of the invention, an operation model constructionsystem includes a data acquisition unit that acquires operating data andexternal environment data of a moving object, an associated dataaccumulation unit that accumulates associated data obtained byclassifying the external environment data into plural items andassociating the operating data with the respective items, and anoperation model construction unit that constructs plural operationmodels to operate the moving object, based on the associated data.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present invention will be described indetail based on the following figures, wherein:

FIG. 1 is a conceptual module configuration view of an exemplaryconfiguration of an exemplary embodiment;

FIG. 2 is a conceptual module configuration view of an exemplaryconfiguration of the exemplary embodiment;

FIG. 3 is a conceptual module configuration view of an exemplaryconfiguration of the exemplary embodiment;

FIG. 4 is a view for explaining an exemplary system configuration usingthe exemplary embodiment;

FIG. 5 is a flow chart illustrating an exemplary processing by theexemplary embodiment;

FIG. 6 is a view for explaining an exemplary processing by an exemplaryembodiment;

FIG. 7 is a view for explaining an exemplary data structure of aclassification table;

FIG. 8 is a view for explaining an exemplary data structure of anassociated data table;

FIG. 9 is a view for explaining an exemplary data structure of a vehiclebody data table;

FIG. 10 is a view for explaining an exemplary data structure of amaintenance data table;

FIG. 11 is a view for explaining an exemplary processing by theexemplary embodiment;

FIG. 12 is a flow chart illustrating an exemplary processing by theexemplary embodiment;

FIG. 13 is a view for explaining an exemplary data structure of atime-series classification table; and

FIG. 14 is a block diagram illustrating an exemplary hardwareconfiguration of a computer to implement the exemplary embodiment.

DETAILED DESCRIPTION

Hereinafter, exemplary embodiments of the present invention will bedescribed with reference to the accompanying drawings.

FIG. 1 illustrates a conceptual module configuration view of anexemplary configuration of an exemplary embodiment.

Meanwhile, a module, in general, indicates a logically separablecomponent such as software (a computer program) or hardware.Accordingly, a module in the present exemplary embodiment indicates notonly a module in a computer program but also a module in a hardwareconfiguration. Hence, descriptions of the present exemplary embodimentsalso include descriptions of a computer program to function as themodule (a program to cause a computer to execute each process, a programto cause a computer to function as each unit, and a program to cause acomputer to implement each function), a system, and a method. Here, forconvenience of descriptions, the expressions “store,” “cause to store,”and equivalent expressions thereto will be used, and when an exemplaryembodiment is a computer program, the expressions indicate causing dataor the like to be stored in a storage device or performing a control tostore data or the like in a storage device. In addition, one module maycorrespond to one function. In implementation, however, one module maybe configured as one program, plural modules may be configured as oneprogram, and in reverse, one module may be configured as pluralprograms. In addition, plural modules may be executed by one computer,or one module may be executed by plural computers in a distributed orparallel environment. In addition, one module may include anothermodule. In addition, hereinafter, the term “connection” is also used ina case of a logical connection (e.g., data exchange, instructions, and areference relationship among data), in addition to a physicalconnection. The term “predetermined” refers to being determined prior toa target processing, and includes the meaning of being determinedaccording to a circumstance/state at or until a specific time pointbefore a processing by the present exemplary embodiment is started, orprior to a target processing even after a processing by the presentexemplary embodiment is started. When plural “predetermined values”exist, the values may be different from each other, or two or more ofthe values (including any values, of course) may be identical to eachother. A description indicating that “when it is A, B is performed” isused to indicate that “whether it is A is determined, and when it isdetermined that it is A, B is performed,” except for a case where thedetermination of whether it is A is unnecessary.

In addition, a system or a device includes a case where the system orthe device is implemented by, for example, one computer, hardwarecomponent, and device, in addition to a case where plural computers,hardware components, devices and others are configured to be connectedto each other by a communication unit such as a network (includingone-to-one corresponding communication connection). The terms “device”and “system” are used to have the same meaning. Of course, the “system”does not include a mere system indicating a social “structure” (socialsystem) which is an artificial engagement.

In addition, target information is read from a storage device perprocessing by each module or for each of plural processings which isexecuted in a module. After the processing is executed, the processingresult is recorded in the storage device. Accordingly, descriptions ofthe reading from the storage device prior to the processing and therecording in the storage device after the processing may be omitted. Inaddition, the storage device may include, for example, a hard disk, arandom access memory (RAM), an external storage medium, a storage devicethrough a communication line, and a register within a central processingunit (CPU).

A model construction system 100 according to the present exemplaryembodiment constructs operation models for use in operation of a movingobject (which may include an automatic operation). As illustrated in theexample of FIG. 1, the model construction system 100 includes a positionmeasuring device 105, an external environment sensor 110, an externalenvironment data acquisition module 115, a sensor 120 measuring a brakepedal force/speed/distance, an operating data acquisition module 125, anexternal environment data classification module 130, an operating dataaccumulation module 135, an operating data DB 140, a vehicle body dataDB 145, a maintenance data DB 150, an operation model constructionmodule 155, and an operation model storage module 160.

Here, the “moving object” may be a vehicle used for a movement of ahuman being or an object and includes, for example, an automobile, atwo-wheeled vehicle, a trolley, ship, a plane, a helicopter, a drone,and a wheel chair. The moving object is equipped therein with the modelconstruction system 100 generating operation models. Hereinafter, anautomobile (an automatic driving vehicle 410) will be described as anexample of the vehicle. The automobile includes, for example, anautomatic driving car and an automobile called, for example, a connectedcar.

The automatic driving car may operate the vehicle itself according tooperation models for an operation of the vehicle, in addition to afunction to collect operating data of the vehicle. Specifically, vehiclecontrol data (specifically, a traveling direction, a vehicle speed, asteering angle and others) for automatic driving of the vehicle aregenerated by applying the operating data collected by the vehicle to theoperation models. The operation of the automatic driving car iscontrolled by the generated vehicle control data.

In order to improve the safety of an automobile (without being limitedto the connected car or the automatic driving car), a driving supportsystem such as an autonomous emergency brake or an active cruise control(ACC), or a cooperative driving support system implemented by avehicle-to-vehicle (V2V) communication such as a cooperative activecruise control (CACC) has been developed. The present exemplaryembodiment may be used for these technologies.

The position measuring device 105 is connected to the externalenvironment data acquisition module 115. The position measuring device105 acquires position data (e.g., the latitude and the longitude) of theautomatic driving vehicle 410. For example, a global positioning system(GPS), a beacon, or an electronic toll collection (ETC) system may beused.

The external environment sensor 110 is connected to the externalenvironment data acquisition module 115. The external environment sensor110 acquires data for an external environment of the automatic drivingvehicle 410. For example, a thermometer, a hygrometer, a barometer, arain gauge, an anemometer, or a distance meter may be used. The distancemeter measures, for example, a distance between the automatic drivingvehicle 410 and an obstacle (an object with which the vehicle maycollide) or the like.

An external environment DB 195 is connected to the external environmentdata acquisition module 115 of the model construction system 100 througha communication line (in general, a wireless line). The externalenvironment DB 195 receives, for example, position data from theexternal environment data acquisition module 115 and transmitsmeteorological information (weather and climate) of the position to theexternal environment data acquisition module 115. The meteorologicalinformation may include past meteorological information and anticipatedfuture meteorological information, in addition to current meteorologicalinformation. Further to the meteorological information itself, themeteorological information may include advisory/warning, information ofa snow accumulation amount and earthquake intensity/sea waves, andothers. In addition, the external environment DB 195 receives theposition data from the external environment data acquisition module 115and transmits road and traffic information of the position to theexternal environment data acquisition module 115. The road and trafficinformation may include, for example, traffic congestion information,traffic regulation information, road guide, and parking lot information.

The external environment data acquisition module 115 is connected to theposition measuring device 105, the external environment sensor 110, theexternal environment data classification module 130, the operating dataaccumulation module 135, and the external environment DB 195. Theexternal environment data acquisition module 115 acquires externalenvironment data of the automatic driving vehicle 410 from the positionmeasuring device 105, the external environment sensor 110, and theexternal environment DB 195, and sends the environment data to theexternal environment data classification module 130 and the operatingdata accumulation module 135. Especially, the external environment dataacquisition module 115 may acquire past external environment data. Forexample, the external environment data acquisition module 115 mayacquire past meteorological information from the external environment DB195. In addition, the external environment data acquisition module 115may acquire past external environment data in different time periods,depending on types of external environment data. For example, pastevery-12-hour data may be acquired for meteorological information, andpast data per 3 hours may be acquired for a temperature. These data maybe acquired from the external environment DB 195. In addition, forexample, past every-hour data may be acquired for a position. To thisend, the history information of the position measuring device 105 may bestored, and the data may be extracted therefrom.

In addition, the external environment data acquisition module 115 mayacquire anticipated future external environment data depending on typesof external environment data. For example, the meteorologicalinformation may include meteorological information after 12 hours. Inaddition, the external environment data acquisition module 115 mayacquire future external environment data in different time periods,depending on types of external environment data, like theabove-described past external environment data. For example, futureevery-12-hour data may be acquired for meteorological information, andfuture data per 3 hours may be acquired for a temperature. These datamay be acquired from the external environment DB 195. In addition, forexample, future every-hour data may be acquired for a position. Thesedata may be calculated from a current speed, direction and others.

The sensor 120 measuring a brake pedal force/speed/distance is connectedto the operating data acquisition module 125. The sensor 120 measuring abrake pedal force/speed/distance acquires operating data of theautomatic driving vehicle 410. For example, a sensor measuring a brakepedal force, a speed, a traveling distance, the number of enginerevolutions, a gear position, an accelerator opening angle, a steeringangle, a traveling direction and others may be used. In addition,operating data such as front and rear inclination angles and left andright inclination angles may be acquired.

The operating data acquisition module 125 is connected to the sensor 120measuring a brake pedal force/speed/distance and the operating dataaccumulation module 135. The operating data acquisition module 125acquires operating data representing a driving status of the automaticdriving vehicle 410 from the sensor 120 measuring a brake pedalforce/speed/distance. For example, when a brake pedal is stepped onduring traveling at a specific position, operating data such as a speedprior to the brake pedal stepping, a speed at the brake releasing time,a brake pedal force, and a braking distance are collected. That is,control data of a brake and a result data thereof (in which distance andto which extent the speed could be reduced) are collected as operatingdata.

The external environment data classification module 130 is connected tothe external environment data acquisition module 115 and the operatingdata accumulation module 135. The external environment dataclassification module 130 acquires the external environment data fromthe external environment data acquisition module 115 and the operatingdata accumulation module 135, and classifies the external environmentdata into plural items. The classification may be performed according topredetermined conditions (conditions belonging to classification items)or using a clustering method. Here, the reason for classifying theexternal environment data is that it is favorable for the control toassume that when external environments are different from each other,operation models determining operation amounts are also different fromeach other. For example, the classification is performed as in aclassification table 700 according to classification conditions. FIG. 7is a view for explaining an exemplary data structure of theclassification table 700. The classification table 700 includes aclassification ID column 710, a weather column 720, a temperature column730, a position column 740 and others. In the present exemplaryembodiment, the classification ID column 710 stores information foruniquely identifying classification (classification ID (identification)and classification item). The weather column 720 stores weather(meteorological) data to be classified into the classification ID. Thetemperature column 730 stores temperature data to be classified into theclassification ID. The position column 740 stores position data to beclassified into the classification ID. That is, when externalenvironment data correspond to data within the weather column 720, thetemperature column 730, the position column 740 and others, the externalenvironment data are classified into the classification ID of theclassification ID column 710 which corresponds to the line of theexternal environment data. In addition, with respect to the description“external environment data correspond to data within the weather column720 and others,” the data within the weather column 720 and others andthe external environment data may be in a relation of being exactlyconsistent with each other, or a difference therebetween may be lessthan or equal to or lower than a predetermined threshold value. When thedata within the weather column 720 and others have a range, the externalenvironment data may be in a relation of being included in the range. Inaddition, as the external environment data classification module 130, anidentifier such as a support vector machine may be used.

The operating data accumulation module 135 is connected to the externalenvironment data acquisition module 115, the operating data acquisitionmodule 125, the external environment data classification module 130, andthe operating data DB 140. The operating data accumulation module 135acquires the operating data and the external environment data of theautomatic driving vehicle 410 from the operating data acquisition module125 and the external environment data acquisition module 115. Theoperating data accumulation module 135 accumulates associated data whichare obtained by associating the operating data with the plural itemsclassified by the external environment data classification module 130,in the operating data DB 140. Specifically, an operating data group isassociated with classification items (classification ID) of an externalenvironment at the time point of acquisition of the operating datagroup, and the associated data are stored in the operating data DB 140.Meanwhile, here, the “time point” includes, in addition to a case wherethe time point of the acquisition of the external environment data andthe time point of the acquisition of the operating data are exactlyidentical to each other, a case where the time points are less than orwithin a predetermined time.

Since the operating data are accumulated while being associated with theclassification items by the operating data accumulation module 135, theoperating data are collected for the respective classification itemsaccording to the conditions of the external environment data so thatsimilar operating data may be acquired under specific environments.

The operating data DB 140 is connected to the operating dataaccumulation module 135 and the operation model construction module 155.The operating data DB 140 stores the associated data that have beengenerated by the operating data accumulation module 135. For example, anassociated data table 800 is stored in the operating data DB 140. FIG. 8is a view for explaining an exemplary data structure of the associateddata table 800. The associated data table 800 includes a vehicle IDcolumn 810, a classification ID column 820, and an operating data column830. The operating data column 830 includes a speed column 832, a brakepedal force column 834, a distance column 836 and others. In the presentexemplary embodiment, the vehicle ID column 810 stores information(vehicle ID) for uniquely identifying a vehicle. The classification IDcolumn 820 stores classification ID (corresponding to the classificationID column 710 of the classification table 700). The operating datacolumn 830 stores operating data at a time point of the classificationinto the classification ID. The speed column 832 stores a speed. Thebrake pedal force column 834 stores a brake pedal force. The distancecolumn 836 stores a distance.

The vehicle body data DB 145 is connected to the operation modelconstruction module 155. The vehicle body data DB 145 stores data forthe automatic driving vehicle 410 including the model constructionsystem 100. For example, the vehicle body data DB 145 stores a vehiclebody data table 900. FIG. 9 is a view for explaining an exemplary datastructure of the vehicle body data table 900. The vehicle body datatable 900 includes a vehicle ID column 910, a manufacturer column 920, avehicle model column 930, a vehicle height column 940, an overall lengthcolumn 950, a width column 960 and others. The vehicle ID column 910stores vehicle ID. The manufacturer column 920 stores a manufacturer ofthe vehicle. The vehicle model column 930 stores a model of the vehicle.The vehicle height column 940 stores a height of the vehicle. Theoverall length column 950 stores an entire length of the vehicle. Thewidth column 960 stores a width of the vehicle. Since these data do notneed to be changed, they are preset. For example, the data are set to,for example, data at the manufacturing time of the automatic drivingvehicle 410. Additionally, a driving system, brake parts, rotor parts,tires and so on may be stored.

The maintenance data DB 150 is connected to the operation modelconstruction module 155. The maintenance data DB 150 stores data for themaintenance of the automatic driving vehicle 410 including the modelconstruction system 100. The maintenance data include, for example, datarepresenting when a work is performed for each part and what work isperformed. For example, a maintenance data table 1000 is stored. FIG. 10is a view for explaining an exemplary data structure of the maintenancedata table 1000. The maintenance data table 1000 includes a vehicle IDcolumn 1010, a work date and time column 1020, a part ID column 1030, awork content column 1040 and others. The vehicle ID column 1010 storesvehicle ID. The work date and time column 1020 stores date and time(year, month, day, hour, minute, second, a fraction of a second, orcombinations thereof) of a work such as a vehicle repair. In the presentexemplary embodiment, the part ID column 1030 stores information (partID) for uniquely identifying each part within a vehicle. The workcontent column 1040 stores work contents of the part. These data areadded when a work such as a repair (including a vehicle examination) ofthe automatic driving vehicle 410 is performed.

The operation model construction module 155 is connected to theoperating data DB 140, the vehicle body data DB 145, the maintenancedata DB 150, and the operation model storage module 160. The operationmodel construction module 155 constructs plural operation models tooperate the automatic driving vehicle 410, based on the associated datawithin the operating data DB 140. In addition, the operation modelconstruction module 155 may construct the plural operation models tooperate the automatic driving vehicle 410, by adding the data within thevehicle body data DB 145 and the maintenance data DB 150.

For example, an operation model to calculate a brake pedal force isconstructed as follows:ax+by+ . . . +cz=brake pedal force  (Equation 1)

Here, a, b, c and others are coefficients. x, y, z and others areoperating data and include, for example, a speed at the braking starttime and a braking distance. This function may be calculated by multipleregression analysis using the operating data as descriptive variablesand the brake pedal force as a target variable. In addition, thefunction is constructed for each classification ID.

As the constructing method of the operation models, for example, machinelearning may be used as well, in addition to the multiple regressionanalysis which is a kind of a multivariate analysis technique.

The operation model storage module 160 is connected to the operationmodel construction module 155. The operation model storage module 160stores the operation models constructed by the operation modelconstruction module 155.

FIG. 2 is a conceptual module configuration view of the exemplaryconfiguration of the present exemplary embodiment.

While the model construction system 100 illustrated in the example ofFIG. 1 constructs operation models, a model use control system 200illustrated in the example of FIG. 2 controls the automatic drivingvehicle 410 by using the operation models constructed in the modelconstruction system 100. In addition, the same components as those ofthe model construction system 100 illustrated in the example of FIG. 1will be denoted by the same reference numerals as used in FIG. 1, andthus, overlapping descriptions thereof will be omitted.

The model use control system 200 includes a position measuring device105, an external environment sensor 110, an external environment dataacquisition module 115, a sensor 120 measuring a brake pedalforce/speed/distance, an operating data acquisition module 125, anexternal environment data classification module 130, an operating dataaccumulation module 135, an operating data DB 140, a vehicle body dataDB 145, a maintenance data DB 150, an operation model storage module160, an operation amount calculation module 265, and a control module270.

The position measuring device 105 is connected to the externalenvironment data acquisition module 115.

The external environment sensor 110 is connected to the externalenvironment data acquisition module 115.

The external environment DB 195 is connected to the external environmentdata acquisition module 115 of the model use control system 200.

The external environment data acquisition module 115 is connected to theposition measuring device 105, the external environment sensor 110, theexternal environment data classification module 130, the operating dataaccumulation module 135, the operation amount calculation module 265,and the external environment DB 195.

The sensor 120 measuring a brake pedal force/speed/distance is connectedto the operating data acquisition module 125.

The operating data acquisition module 125 is connected to the sensor 120measuring a brake pedal force/speed/distance and the operating dataaccumulation module 135.

The external environment data classification module 130 is connected tothe external environment data acquisition module 115, the operating dataaccumulation module 135, and the operation amount calculation module265.

The operating data accumulation module 135 is connected to the externalenvironment data acquisition module 115, the operating data acquisitionmodule 125, the external environment data classification module 130, andthe operating data DB 140.

The operating data DB 140 is connected to the operating dataaccumulation module 135 and the operation amount calculation module 265.

The vehicle body data DB 145 is connected to the operation amountcalculation module 265.

The maintenance data DB 150 is connected to the operation amountcalculation module 265.

The operation model storage module 160 is connected to the operationamount calculation module 265.

The operation amount calculation module 265 is connected to the externalenvironment data acquisition module 115, the external environment dataclassification module 130, the operating data DB 140, the vehicle bodydata DB 145, the maintenance data DB 150, the operation model storagemodule 160, and the control module 270. The operation amount calculationmodule 265 calculates an operation amount for traveling of the automaticdriving vehicle 410, by extracting an applicable operation model fromthe operation model storage module 160 according to the classificationresult of the external environment data classification module 130, andapplying the environment data (operating data necessary for theoperation model) from the operating data DB 140 to the operation model.For example, the operation amount is calculated according to a currentspeed of the automatic driving vehicle 410, a speed at a target positionafter speed adjustment, and a distance to the target position.Specifically, the brake pedal force is calculated as an operation amountby using Equation 1 above. In addition, the brake pedal force iscalculated by applying the vehicle body data, the vehicle bodymaintenance data, and the operating data (e.g., the current speed and adistance to an obstacle) to the operation model of the brake pedalforce.

The control module 270 is connected to the operation amount calculationmodule 265. The control module 270 controls each part (system) withinthe automatic driving vehicle 410 according to the operation amountcalculated by the operation amount calculation module 265. For example,the brake of the automatic driving vehicle 410 is controlled accordingto the operation amount of the brake pedal force.

FIG. 3 is a conceptual module configuration view of the exemplaryconfiguration of the present exemplary embodiment.

While the model construction system 100 illustrated in the example ofFIG. 1 constructs operation models, and the model use control system 200illustrated in the example of FIG. 2 controls the automatic drivingvehicle 410 by using the operation models constructed by the modelconstruction system 100, a model construction/control system 300illustrated in the example of FIG. 3 is a combination of the modelconstruction system 100 and the model use control system 200. The modelconstruction/control system 300 constructs operation models and controlsthe automatic driving vehicle 410 by using the constructed operationmodels. In addition, the same components as those of the modelconstruction system 100 illustrated in the example of FIG. 1 and themodel use control system 200 illustrated in the example of FIG. 2 willbe denoted by the same reference numerals as used in FIGS. 1 and 2, andthus, overlapping descriptions thereof will be omitted.

The model construction/control system 300 includes a position measuringdevice 105, an external environment sensor 110, an external environmentdata acquisition module 115, a sensor 120 measuring a brake pedalforce/speed/distance, an operating data acquisition module 125, anexternal environment data classification module 130, an operating dataaccumulation module 135, an operating data DB 140, a vehicle body dataDB 145, a maintenance data DB 150, an operation model constructionmodule 155, an operation model storage module 160, an operation amountcalculation module 265, and a control module 270.

The position measuring device 105 is connected to the externalenvironment data acquisition module 115.

The external environment sensor 110 is connected to the externalenvironment data acquisition module 115.

The external environment DB 195 is connected to the external environmentdata acquisition module 115 of the model construction/control system300.

The external environment data acquisition module 115 is connected to theposition measuring device 105, the external environment sensor 110, theexternal environment data classification module 130, the operating dataaccumulation module 135, the operation amount calculation module 265,and the external environment DB 195.

The sensor 120 measuring a brake pedal force/speed/distance is connectedto the operating data acquisition module 125.

The operating data acquisition module 125 is connected to the sensor 120measuring a brake pedal force/speed/distance and the operating dataaccumulation module 135.

The external environment data classification module 130 is connected tothe external environment data acquisition module 115, the operating dataaccumulation module 135, and the operation amount calculation module265.

The operating data accumulation module 135 is connected to the externalenvironment data acquisition module 115, the operating data acquisitionmodule 125, the external environment data classification module 130, andthe operating data DB 140.

The operating data DB 140 is connected to the operating dataaccumulation module 135, the operation model construction module 155,and the operation amount calculation module 265.

The vehicle body data DB 145 is connected to the operation modelconstruction module 155 and the operation amount calculation module 265.

The maintenance data DB 150 is connected to the operation modelconstruction module 155 and the operation amount calculation module 265.

The operation model construction module 155 is connected to theoperating data DB 140, the vehicle body data DB 145, the maintenancedata DB 150, and the operation model storage module 160.

The operation model storage module 160 is connected to the operationmodel construction module 155 and the operation amount calculationmodule 265.

The operation amount calculation module 265 is connected to the externalenvironment data acquisition module 115, the external environment dataclassification module 130, the operating data DB 140, the vehicle bodydata DB 145, the maintenance data DB 150, the operation model storagemodule 160, and the control module 270.

The control module 270 is connected to the operation amount calculationmodule 265.

FIG. 4 is a view for explaining an exemplary system configuration usingthe present exemplary embodiment.

A model construction system 100 of an automatic driving vehicle 410A, amodel use control system 200 of an automatic driving vehicle 410B, amodel construction/control system. 300 of an automatic driving vehicle410C, a model construction/distribution server 450, and an externalenvironment providing server 480 are connected to each other through acommunication line 490. The communication between the communication line490 and the automatic driving vehicle 410 is a wireless communication.However, the communication line 490 may be a wireless communicationline, a wired communication line, or a combination thereof, and may be,for example, the Internet as a communication infrastructure. Inaddition, the function by the model construction/distribution server 450and the external environment providing server 480 may be implemented asa cloud service.

The automatic driving vehicle 410A includes the model constructionsystem 100. The automatic driving vehicle 410B includes the model usecontrol system 200. The automatic driving vehicle 410C includes themodel construction/control system 300. The external environmentproviding server 480 includes the external environment DB 195.

The model construction/distribution server 450 has the functionequivalent to that of the model construction system 100 illustrated inthe example of FIG. 1, and constructs operation models to distribute theoperation models to each automatic driving vehicle 410. The modelconstruction/distribution server 450 includes a model constructionsystem 100, a data collection module 455, and a model distributionmodule 460. Here, the model construction system 100 is connected to thedata collection module 455 and the model distribution module 460. Ofcourse, the position measuring device 105, the external environmentsensor 110, the sensor 120 measuring a brake pedal force/speed/distanceand others are unnecessary for the model construction system 100 withinthe model construction/distribution server 450.

The data collection module 455 is connected to the model constructionsystem 100. The data collection module 455 collects data (specifically,the data acquired by the position measuring device 105, and the externalenvironment sensor 110, the sensor 120 measuring a brake pedalforce/speed/distance and others, and the data within the externalenvironment DB 195) from each automatic driving vehicle 410.

The model distribution module 460 is connected to the model constructionsystem 100. The model distribution module 460 distributes the operationmodels constructed by the model construction system 100 to eachautomatic driving vehicle 410.

Each automatic driving vehicle 410 controls, for example, travelingaccording to the operation models constructed by the automatic drivingvehicle 410 itself or the operation models transmitted from otherdevices (the model construction system 100 and the modelconstruction/distribution server 450 within the automatic drivingvehicle 410A).

FIG. 5 is a flow chart illustrating an exemplary processing by thepresent exemplary embodiment.

In step S502, the operating data acquisition module 125 acquiresoperating data of the automatic driving vehicle 410 from the sensor 120measuring a brake pedal force/speed/distance and others.

In step S504, the external environment data acquisition module 115acquires external environment data from the position measuring device105, the external environment sensor 110, and the external environmentDB 195.

In step S506, the external environment data classification module 130performs a classification according to the external environment data.The classification will be described by using the specific exampleillustrated in FIG. 6. FIG. 6 is a view for explaining an exemplaryprocessing by the present exemplary embodiment. FIG. 6 represents anexample of a classification by a tree-structure branching process(decision tree). Here, examples of the external environment data areweather, a temperature and others.

In a layer 610, the classification is performed according to weather(meteorological information). Specifically, a case of the condition“weather=sunny” is classified into a node 612, a case of the condition“weather=rainy” is classified into a node 614, and a case of thecondition “weather=snowy” is classified into a node 616.

In a layer 620, the classification is performed according to atemperature. A case belonging to the node 614 and meeting the condition“15<temperature≤20” is classified into a node 622, and a case belongingto the node 614 and meeting the condition “20<temperature≤25” isclassified into a node 624.

A layer 690 represents the classification result. For example, a node694 representing the classification items includes “weather=rainy,”“15<temperature≤20,” . . . .

In step S508, the operating data accumulation module 135 accumulatesoperating data and others for each classification item in the operatingdata DB 140.

In step S510, the operation model construction module 155 constructs anoperation model for each classification item.

In step S512, the operation model storage module 160 stores theoperation model.

FIG. 11 is a view for explaining an exemplary processing by the presentexemplary embodiment (the processing of the flow chart illustrated inthe example of FIG. 5).

An external environment data storage module 1110 stores externalenvironment data (e.g., position data and weather data) acquired by theexternal environment data acquisition module 115.

A classification is performed according to the external environment datawithin the external environment data storage module 1110. For example,classification A 1120 is a classification item meeting the condition“East Longitude: 130-131, North Latitude: 35-36, Temperature: 15-20, andWeather: Sunny.” Classification B 1130 is a classification item meetingthe condition of “East Longitude: 130-131, North Latitude: 35-36,Temperature: 20-25, and Weather: Sunny.” Classification C 1140 is aclassification item meeting the condition of “East Longitude: 130-131,North Latitude: 35-36, Temperature: 15-20, and Weather: Rainy.”

Then, an operation model is constructed by using the operating datacorresponding to each of the classification items (classifications A1120, B 1130, or C 1140). An operation model is constructed for eachclassification item. Specifically, operation model A 1125 correspondingto classification A 1120, operation model B 1135 corresponding toclassification B 1130, and operation model C 1145 corresponding toclassification C 1140 are constructed. In addition, the operation modelsmay be constructed by further using the vehicle body data within thevehicle body data DB 145 and the maintenance data within the maintenancedata DB 150, in addition to the operating data. Specifically, anoperation model which anticipates an appropriate brake pedal force isconstructed for each classification.

FIG. 12 is a flow chart illustrating an exemplary processing by thepresent exemplary embodiment (the model use control system 200). Here,operation models have already been constructed, and the traveling of theautomatic driving vehicle 410 is controlled by using the operationmodels.

In step S1202, the operating data acquisition module 125 acquiresoperating data.

In step S1204, the external environment data acquisition module 115acquires external environment data.

In step S1206, the external environment data classification module 130performs a classification according to the external environment data.

In step S1208, the operation amount calculation module 265 extractsoperation models corresponding to classification items.

In step S1210, the operation amount calculation module 265 calculates anoperation amount by applying the operating data and others to theoperation models.

In step S1212, the control module 270 operates the vehicle according tothe operation amount.

FIG. 13 is a view illustrating an exemplary data structure of atime-series classification table 1300. Descriptions will be made on acase where operation models are constructed by using past environmentdata. The external environment data acquisition module 115 prepares thetime-series classification table 1300. Specifically, the externalenvironment data acquired by the external environment data acquisitionmodule 115 are stored as a history so that after lapse of X hour (s),the acquired external environment data become the external environmentdata acquired X hour(s) ago.

The time-series classification table 1300 includes a classification IDcolumn 1310, a time-series weather column 1320, a time-seriestemperature column 1330, a time-series position column 1340 and others.The time-series weather column 1320 includes a current column 1322, a 12hours ago column 1324, and a 24 hours ago column 1326. The time-seriestemperature column 1330 includes a current column 1332, a 3 hours agocolumn 1334, and a 6 hours ago column 1336. The time-series positioncolumn 1340 includes a current column 1342, a 1 hour ago column 1344,and a 2 hours ago column 1346. The time-series classification table 1300is extended from the classification table 700 illustrated in the exampleof FIG. 7 to incorporate time-series external environments.

The classification ID column 1310 stores classification ID. Thetime-series weather column 1320 stores time-series weather to beclassified into the classification ID. The current column 1322 storescurrent weather. The 12 hours ago column 1324 stores weather 12 hoursago. The 24 hours ago column 1326 stores weather 24 hours ago. Thetime-series temperature column 1330 stores a time-series temperature tobe classified into the classification ID. The current column 1332 storesa current temperature. The 3 hours ago column 1334 stores a temperature3 hours ago. The 6 hours ago column 1336 stores a temperature 6 hoursago. The time-series position column 1340 stores a time-series positionto be classified into the classification ID. The current column 1342stores a current position. The 1 hour ago column 1344 stores a position1 hour ago. The 2 hours ago column 1346 stores a position 2 hours ago.

In addition, a time-series classification table having a data structureequivalent to that of the time-series classification table 1300(specifically, having anticipated future external environment datacolumns) may be generated by acquiring external environment data(weather forecast data) anticipated by the external environmentproviding server 480.

Accordingly, the external environment data classification module 130performs a classification by using past or future time-series externalenvironment data, and the operation model construction module 155constructs an operation model for each classification. Therefore, theautomatic driving vehicle 410 may be controlled according to anoperation model appropriate for an external environment having a timeperiod. Specifically, in a case where the current weather is “sunny,”and the weather of the previous day is “snowy,” the control according tothe external environment may be favorably performed, as compared to anoperation model for a case where the current weather is simply “sunny.”

In addition, the hardware configuration of the computers in which theprograms as the present exemplary embodiment are executed is generalcomputers as illustrated in FIG. 14, and specifically, embeddedcomputers (also called a control computer, e.g., an electronic/enginecontrol unit (ECU)), computers serving as servers, or the like. That is,as a specific example, a CPU 1401 is used as a processor (arithmeticunit), a RAM 1402, a ROM 1403, and an HD 1404 are used as storagedevices. As for HD 1404, for example, a hard disk or a solid state drive(SSD) may be used. The hardware configuration includes the CPU 1401which executes the programs such as the external environment dataacquisition module 115, the operating data acquisition module 125, theexternal environment data classification module 130, the operating dataaccumulation module 135, the operation model construction module 155,the operation amount calculation module 265, and the control module 270,the RAM 1402 which stores the programs or data, the ROM 1403 whichstores a program to start the computer and others, the HD 1404 which isan auxiliary storage device (that may be, for example, a flash memory)having the functions of the operating data DB 140, the vehicle body dataDB 145, the maintenance data DB 150, and the operation model storagemodule 160, an reception device 1406 which receives data based on auser's operation of a touch screen, a microphone, a keyboard, a mouse orthe like or data from the position measuring device 105, the externalenvironment sensor 110, the sensor 120 measuring a brake pedalforce/speed/distance and others, an output device 1405 which outputscontrol data to a liquid crystal display, a loudspeaker, or each partwithin the automatic driving vehicle 410 by the processing of thecontrol module 270, a communication line interface 1407 for connectionto a communication network, such as a network interface card, and a bus1408 which connects the above-described components to each other forexchange of data. These computers may be connected to each other byplural interconnection networks.

Among the above-described exemplary embodiments, the exemplaryembodiments relating to computer programs are implemented by causing thecomputer programs as software to be read into the present hardwareconfiguration system, and causing the software and the hardwareresources to cooperate with each other. For example, the computerprograms may be equipped on the operation system (OS) for a vehiclecontrol, or inside the vehicle control OS.

In addition, the hardware configuration illustrated in FIG. 14 is anexemplary configuration. The exemplary embodiments of the presentinvention are not limited to the configuration illustrated in FIG. 14,and may have any configuration that enables the execution of the modulesdescribed in the exemplary embodiments of the present invention. Forexample, a portion of the modules may be configured as dedicatedhardware (e.g., an application specific integrated circuit (ASIC) for aspecific use), and a portion of the modules may be provided within anexternal system and connected to the other modules through acommunication line. In addition, the systems illustrated in FIG. 14 maybe connected to each other by plural interconnection communication linesto operate in cooperation with each other.

In addition, the above-described programs may be provided by beingstored in a recording medium or the programs may be provided by acommunication unit. In this case, for example, the above-describedprogram may be construed as an invention of a “computer readablerecording medium recording a program.”

The “computer readable recording medium storing a program” indicates acomputer readable recording medium storing a program, which is usefulfor installation, execution, distribution and others of a program.

In addition, the recording medium is, for example, a digital versatiledisc (DVD) such as “DVD-R, DVD-RW, and DVD-RAM” which are formatsdefined in the DVD forum, and “DVD+R and DVD+RW” which are formatsdefined for DVD+RW, a compact disc (CD) such as a CD read only memory(CD-ROM), a CD recordable (CD-R), and a CD rewritable (CD-RW), aBlu-ray® disc, a magneto-optical (MO) disc, a flexible disc (FD), amagnetic tape, a hard disc, a read-only memory (ROM), an electricallyerasable and programmable read-only memory (EEPROM®), a flash memory, arandom access memory (RAM), and a secure digital (SD) memory card.

In addition, all or some of the above-described programs may be saved ordistributed by being recorded in the recording medium. The programs maybe caused to be transmitted by a communication using a transmissionmedium such as a wired network, a wireless communication network, or acombination thereof used for a local area network (LAN), a metropolitanarea network (MAN), a wide area network (WAN), the Internet, theIntranet, the Extranet and others. In addition, the programs may becarried by carrier waves.

Furthermore, the above-described programs may be some or the entirety ofother programs, or may be recorded together with separate programs in arecording medium. In addition, the programs may be divided and recordedin plural recording media. In addition, the programs may be recorded inany form, such as compression or encryption, as long as the programs inthat form may be restored.

The foregoing description of the exemplary embodiments of the presentinvention has been provided for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Obviously, many modificationsand variations will be apparent to practitioners skilled in the art. Theembodiments were chosen and described in order to best explain theprinciples of the invention and its practical applications, therebyenabling others skilled in the art to understand the invention forvarious embodiments and with the various modifications as are suited tothe particular use contemplated. It is intended that the scope of theinvention be defined by the following claims and their equivalents.

What is claimed is:
 1. An operation model construction servercomprising: a processor programmed to: acquire operating data andexternal environment data of each of a plurality of moving objects, eachmoving object being connected to the operation model construction serverthrough a communication line; classify the external environment datainto a plurality of classes and associate the operating data with arespective one of the plurality of classes; construct a plurality ofoperation models to operate each of the plurality of moving objectsbased on the operating data associated with the respective one of theplurality of classes; and distribute the plurality of operation modelsto each of the plurality of moving objects.
 2. The operation modelconstruction server according to claim 1, wherein the processor isfurther programmed to: calculate an operation amount for a respectiveone of the plurality of moving objects according to a current speed ofthe respective moving object, a speed at a target position after a speedadjustment, and a distance to the target position.
 3. The operationmodel construction server according to claim 1, wherein the processor isprogrammed to acquire past external environment data of each of theplurality of moving objects.
 4. The operation model construction serveraccording to claim 3, wherein the processor is programmed to acquire thepast external environment data in different time periods, depending ontypes of the external environment data.
 5. The operation modelconstruction server according to claim 3, wherein the processor isprogrammed to acquire anticipated future external environment data,depending on types of the external environment data.
 6. The operationmodel construction server according to claim 3, wherein the pastexternal environment data includes at least one of past position data ofeach of the plurality of moving objects and past meteorological data. 7.The operation model construction server according to claim 1, whereineach of the plurality of moving objects is one selected from the groupconsisting of an automobile, a two-wheeled vehicle, a trolley, a ship, aplane, a helicopter, a drone, and a wheel chair.
 8. The operation modelconstruction server according to claim 1, wherein the externalenvironment data includes at least one of position data of the movingobject and meteorological data.
 9. The operation model constructionserver according to claim 1, wherein one of the plurality of operationmodels is configured to calculate a brake pedal force.
 10. Anon-transitory computer readable storage medium storing a program thatcauses a computer to execute operation model construction processing,the processing comprising: acquiring operating data and externalenvironment data of each of a plurality of moving objects, each movingobject being connected to an operation model construction serverincluding the computer through a communication line; classifying theexternal environment data into a plurality of classes and associatingthe operating data with a respective one of the plurality of classes;constructing a plurality of operation models to operate each of theplurality of moving objects based on the operating data associated withthe respective one of the plurality of classes; and distributing theplurality of operation models to each of the plurality of movingobjects.
 11. An automatic moving object comprising: a processorprogrammed to: obtain, from a sensor, operating data and externalenvironment data of the moving object; transmit the operating data andthe external environment data to an operation model construction server;receive a plurality of operation models from the operation modelconstruction server, the plurality of operation models being constructedbased on the operating data and the external environment data; andcontrol automatic movement of the moving object based on the receivedplurality of operation models.